drawio

bahayonghang/drawio-skills · skills.sh
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Skill publicada por bahayonghang/drawio-skills no skills.sh. Instale com: npx skills add bahayonghang/drawio-skills@drawio
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Kind: Agent skills
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Publisher: bahayonghang
Origin: skillssh
Category: ferramentas
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Last push: 2026-09-08T02:57:46Z
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Language: JavaScript
License: MIT
Added: 2026-08-30 15:21:20
Updated: 2026-09-08 15:02:15
Origin id: bahayonghang/drawio-skills/drawio
README

# Draw.io Skill for Claude & Codex

[![Deploy Docs](https://github.com/bahayonghang/drawio-skills/actions/workflows/deploy-docs.yml/badge.svg)](https://github.com/bahayonghang/drawio-skills/actions/workflows/deploy-docs.yml)
[![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](https://spdx.org/licenses/MIT.html)

> **Important**: Draw.io Skill is a **YAML-first, offline-first base workflow**. The default path is local generation through `YAML/CLI -> .drawio + sidecars`, optionally enhanced by draw.io Desktop for PNG/PDF/JPG and embedded SVG export. The [next-ai-draw-io](https://github.com/DayuanJiang/next-ai-draw-io) MCP server (`@next-ai-drawio/mcp-server`) is optional **live refinement** for the base skill only, not a hard dependency.
>
> **Recommendation for Diagram Replication**: For replicating draw.io diagrams, using the `dev` branch of [drawio-scientific-illustrator](https://github.com/bahayonghang/drawio-scientific-illustrator/tree/dev) produces significantly better results than using this skills package.

[English](./README.md) | [中文文档](./README_CN.md) | [Documentation](https://bahayonghang.github.io/drawio-skills/)

Draw.io Skill is a YAML-first draw.io authoring system for engineering diagrams, network diagrams, structured redraws, Mermaid/CSV conversion, and imported `.drawio` files. Publication-facing work is handled by an Academic Overlay that depends on the sibling base skill instead of copying its runtime.

## Recommended Models

- **GPT Sol Max**
- **Claude Fable 5**
- **Claude Opus 5**

## Skill Variants

- `skills/drawio`: **Draw.io Base Skill**. Owns shared execution primitives: the CLI, schemas, general references, themes (including `academic`/`academic-color`), general examples, style presets, Desktop export helpers, diagrams.net URL fallback, and optional live refinement backend.
- `skills/drawio-academic-skills`: **Academic Overlay**. Owns academic policy and academic-specific assets: publication overlay docs (`academic-figure-playbook.md`, `academic-export-checklist.md`), paper/pipeline examples, README, and evals. It requires sibling `../drawio` for execution and never requires MCP/live backend.

Boundary rule: themes and shared execution primitives live in the base; academic policy, academic docs, and paper examples live in the overlay. A standalone academic package can be generated later by a packaging workflow, but the repository model is base plus overlay.

## Features

- **YAML-first artifact bundle**: keep `.drawio`, `.spec.yaml`, and `.arch.json` aligned for repeatable local editing.
- **Desktop-aware export**: use draw.io Desktop for PNG, PDF, JPG, and embedded `.drawio.svg` when available.
- **Optional live refinement**: configure next-ai MCP only for base-skill browser refinement; academic overlay stays offline.
- **3 core routes**: `create`, `edit`, and `replicate`.
- **7 built-in themes**: `tech-blue`, `academic`, `academic-color`, `nature`, `dark`, `arch-dark`, `high-contrast`. `arch-dark` carries the architecture design language adapted from architecture-diagram-generator (MIT, Cocoon AI).
- **15 built-in palettes**: academic, engineering, and general color groups compose independently with themes and carry colorblind, grayscale, category-capacity, and source metadata.
- **Academic overlay policy**: venue/audience preflight, caption/legend checks, formula fidelity, A4/Word/LaTeX expectations, and figure typing.
- **Academic figure taxonomy**: publication requests classify into `architecture`, `roadmap`, or `workflow` before layout and export.
- **Cloud and stencil support**: AWS, GCP, Azure, Kubernetes, and network/provider icon workflows through the base references.
- **Embedded AI, brand, and Lucide icons**: use 309 licensed offline `lobe.*` / `ai.*` AI/LLM logos, `brand.redis`, and a curated `lucide.*` set for common semantic roles without runtime network access. SysML (`mxgraph.sysml.*`) and BPMN (`mxgraph.bpmn.*`) base names are searchable too.
- **Network topology support**: semantic device types (`router`, `switch`, `firewall`, `server`, `load_balancer`, `subnet`, `internet`, `ap`) and automatic link labels from interface/IP/VLAN/bandwidth metadata.
- **Offline config and IaC import**: turn declared Terraform, Kubernetes, Compose, SQL DDL, OpenAPI, GitHub Actions, or GitLab CI into a canonical diagram — no provider CLI, Graphviz, or network.
- **Code relationship import**: render Python, JavaScript/TypeScript, Go, or Rust module/class relationships from a local project directory.
- **Live snapshots and drift**: project saved Terraform state, Docker inspect, or Kubernetes live JSON, and compare a declared-vs-live projection to render architecture drift.
- **Multi-page bundles and postprocess**: author canonical bundle v1 with stable page/object identity, and project or transform diagrams offline with `mermaid`, `explain`, `relabel`, `restyle`, `heatmap`, or script-free `html`.
- **Local PNG/JPEG assets**: register files under top-level `assets` and place them with `node.image`. Paths are relative to `--asset-root` (default cwd). SVG and multi-page `assets` are out of v1.
- **Import and normalize existing diagrams**: convert `.drawio` into a YAML-first bundle with `--input-format drawio --export-spec` (add `--all-pages` for multi-page bundles; add `--extract-assets` for foreign embedded rasters).
- **Validation before export**: structure, layout, quality, formula, and replication text-position checks.

## Runtime Model

Use this order unless the request explicitly needs a browser session:

1. **Offline Authoring Path**: generate `.drawio` locally and keep sidecars in sync.
2. **Desktop-Enhanced Export**: use draw.io Desktop for raster/PDF and embedded SVG exports.
3. **Live Refinement Backend**: base-skill browser refinement only; the offline bundle remains canonical.
4. **Direct XML Exception**: tiny XML-only handoff or exact mxGraph control when YAML is not the right tool.

Academic overlay uses the first two paths only. It does not create, require, or route through `.mcp.json`, MCP, or live backend.

## Install

### Project-level Installation for Diagram Replication (Recommended)

To replicate draw.io diagrams with superior fidelity, install [drawio-scientific-illustrator](https://github.com/bahayonghang/drawio-scientific-illustrator/tree/dev) (`dev` branch) at the project level (which works better for replication than this skills package):

- **Claude (Project Level)**:

  ```bash
  git clone -b dev https://github.com/bahayonghang/drawio-scientific-illustrator.git .claude/skills/drawio-scientific-illustrator
  ```

- **Codex (Project Level)**:

  ```bash
  git clone -b dev https://github.com/bahayonghang/drawio-scientific-illustrator.git .codex/skills/drawio-scientific-illustrator
  ```

### Standard Base Skill Installation

```bash
npx skills add bahayonghang/drawio-skills
```

Restart your client after installation so it reloads the skills.

### Manual

1. Clone the repository.
2. Copy `skills/drawio` into your client's skill directory.
3. For publication-facing workflows, also copy `skills/drawio-academic-skills` next to `drawio` so the overlay can resolve sibling `../drawio`.

Common locations:

- **Claude**
  - macOS: `~/Library/Application Support/Claude/skills/`
  - Linux: `~/.config/Claude/skills/`
  - Windows: `%APPDATA%\Claude\skills\`
- **Codex**
  - macOS / Linux: `~/.codex/skills/`
  - Windows: `%USERPROFILE%\.codex\skills\`

## Optional Live Editing Setup

Normal create/edit/export work does **not** require MCP. Configure `@next-ai-drawio/mcp-server` only when you want base-skill browser refinement.

Academic overlay does not need this setup.

### Claude JSON config

macOS / Linux:

```json
{
  "mcpServers": {
    "drawio": {
      "command": "npx",
      "args": ["--yes", "@next-ai-drawio/mcp-server@latest"]
    }
  }
}
```

Windows:

```json
{
  "mcpServers": {
    "drawio": {
      "type": "stdio",
      "command": "cmd",
      "args": ["/c", "npx", "--yes", "@next-ai-drawio/mcp-server@latest"]
    }
  }
}
```

### Codex `config.toml`

macOS / Linux:

```toml
[mcp_servers.drawio]
command = "npx"
args = ["--yes", "@next-ai-drawio/mcp-server@latest"]
```

Windows:

```toml
[mcp_servers.drawio]
type = "stdio"
command = "cmd"
args = ["/c", "npx", "--yes", "@next-ai-drawio/mcp-server@latest"]
```

## Quick Start

Create a new diagram:

```text
/drawio create a horizontal tech-blue login flow with 6 nodes
```

Create a network topology with structured metadata:

```text
/drawio create a tech-blue network topology with a firewall, core switch, two app servers, and a private database subnet. Label interfaces and VLANs on the links.
```

Create a publication figure with the overlay:

```text
/drawio-academic-skills create an IEEE-style workflow figure for a manuscript. Deliver .drawio + .spec.yaml + .arch.json + .svg.
```

Import an existing `.drawio` file into the offline bundle:

```bash
node skills/drawio/scripts/cli.js existing.drawio --input-format drawio --export-spec --write-sidecars
```

Render and validate a bundle:

```bash
node skills/drawio/scripts/cli.js input.yaml output.drawio --validate --write-sidecars
node skills/drawio/scripts/cli.js input.yaml output.svg --validate --write-sidecars
```

Use mixed provider, Lobe, brand, and Lucide icons:

```yaml
nodes:
  - id: lambda
    label: AWS Lambda
    icon: aws.lambda
  - id: openai
    label: OpenAI document understanding
    icon: lobe.openai
  - id: claude
    label: Claude reasoning
    icon: ai.anthropic
  - id: redis
    label: Redis cache
    icon: brand.redis
  - id: cache
    label: Cache fallback
    icon: lucide.database-zap
  - id: ops
    label: Server operations
    icon: lucide.server-cog
```

Common `lobe.*` / `ai.*` icons such as OpenAI, Claude, and Gemini are embedded
as normalized SVGs for reliable offline rendering. Unsupported Lobe names fail
shape validation instead of creating remote image links. `brand.*` is for the
bundled non-AI brand fallbacks; the curated `lucide.*` set is embedded as data
URI SVGs and should not be treated as official brand logos. Supported examples
include `lucide.alarm-clock`, `lucide.server-cog`, and `lucide.workflow`.
Lobe and Lucide attribution files ship under `skills/drawio/assets/licenses/`.

Academic overlay still uses the sibling base CLI:

```bash
node skills/drawio/scripts/cli.js skills/drawio-academic-skills/references/examples/system-architecture-paper.yaml academic-system.svg --validate --write-sidecars --strict-warnings
```

Use draw.io Desktop when you need raster or PDF export:

```bash
node skills/drawio/scripts/cli.js input.yaml output.pdf --validate --use-desktop
node skills/drawio/scripts/cli.js input.yaml output.png --validate --use-desktop
```

Generate a diagrams.net URL fallback from a `.drawio` file:

```bash
node skills/drawio/scripts/runtime/diagrams-net-url.js output.drawio
```

## Canonical Artifact Bundle

When the diagram will continue evolving, keep these files together:

- `<name>.drawio`
- `<name>.spec.yaml`
- `<name>.arch.json`

Academic overlay adds standalone SVG as part of the default publication bundle:

- `<name>.svg`

PNG/PDF/JPG are Desktop-enhanced optional outputs and should be reported as unavailable if draw.io Desktop is missing.

## Network Topology Authoring

The current network-topology workflow supports:

- semantic node types such as `router`, `switch`, `firewall`, `server`, `load_balancer`, `subnet`, `internet`, and `ap`
- link metadata fields such as `srcInterface`, `dstInterface`, `ip`, `vlan`, `bandwidth`, and `linkType`
- layout intents `hierarchical`, `star`, and `mesh`
- provider-aware icon mapping through explicit `icon` fields or `network.vendor` + `network.device`

Representative specs ship in `skills/drawio/references/examples/`.

Render one directly:

```bash
node skills/drawio/scripts/cli.js skills/drawio/references/examples/vendor-device-mapping.yaml output.drawio --validate --write-sidecars
```

## Offline Importers and Adapters

Beyond `create` / `edit` / `replicate`, the offline base promotes a batch of upstream capabilities behind the same canonical boundary. Every route normalizes its input to canonical YAML or multi-page bundle v1 before validation, JavaScript ELK layout, and the renderer — no provider CLI, Graphviz, network, Desktop, browser, MCP, or model is required. Optional parsers and exports report precise missing dependencies or fallbacks.

| Route              | Input                                                                       | `--input-format` / command                                                                  |
| ------------------ | --------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------- |
| `config-import`    | Terraform, Kubernetes, Compose, SQL DDL, OpenAPI, GitHub Actions, GitLab CI | `terraform` / `kubernetes` / `compose` / `sql` / `openapi` / `github-actions` / `gitlab-ci` |
| `code-import`      | local Python, JS/TS, Go, Rust project directory                             | `python-imports` / `python-classes` / `js-imports` / `go-imports` / `rust-imports`          |
| `live-drift`       | saved Terraform state, Docker inspect, Kubernetes live JSON                 | snapshot adapters + `compareGraphProjections`                                               |
| `multi-page`       | canonical bundle v1                                                         | `--input-format drawio --all-pages --export-spec`                                           |
| `raster-replicate` | trusted structured visual extraction                                        | `raster-extraction`                                                                         |
| `postprocess`      | canonical YAML / `.drawio`                                                  | `postprocess mermaid\|explain\|relabel\|restyle\|heatmap\|html`                             |

The shipped postprocess operations are exactly `mermaid`, `explain`, `relabel`, `restyle`, `heatmap`, and script-free `html`; runbook, animated SVG, tube/sequence layout, compression, buildup, PPTX, timelapse, and PR diff are deferred, not hidden commands. Deterministic paths are command evidence; Desktop, provider, browser/MCP, and visual-model runs remain reported as missing evidence when not executed. The full upstream job-to-capability map lives at `skills/drawio/references/docs/upstream-capability-compatibility.md`.

## Documentation

- [Getting Started](https://bahayonghang.github.io/drawio-skills/guide/getting-started)
- [Workflows](https://bahayonghang.github.io/drawio-skills/guide/workflows)
- [Config and IaC Importers](https://bahayonghang.github.io/drawio-skills/guide/config-importers)
- [Code Relationship Importers](https://bahayonghang.github.io/drawio-skills/guide/code-importers)
- [Live Snapshots and Drift](https://bahayonghang.github.io/drawio-skills/guide/live-drift)
- [Multi-page Bundles](https://bahayonghang.github.io/drawio-skills/guide/multi-page)
- [Postprocess Suite](https://bahayonghang.github.io/drawio-skills/guide/postprocess)
- [Upstream Capability Map](https://bahayonghang.github.io/drawio-skills/api/upstream-capability-map)
- [CLI Tool](https://bahayonghang.github.io/drawio-skills/guide/cli)
- [Optional MCP Tools](https://bahayonghang.github.io/drawio-skills/api/mcp-tools)
- [Examples](https://bahayonghang.github.io/drawio-skills/examples/)

## Development

```bash
npm install
npm test
npm run docs:build
```

Repository layout:

- `skills/drawio/`: base skill, CLI, references, themes, schemas, examples, style presets
- `skills/drawio-academic-skills/`: academic overlay, README, evals, publication references
- `docs/`: VitePress site
- `tests/`: repo-level integration tests

## Upstream Relationship

This repository builds on draw.io and the optional **[next-ai-draw-io](https://github.com/DayuanJiang/next-ai-draw-io)** MCP server, but wraps shared behavior in a YAML-first workflow with offline sidecars, design-system references, and route-specific guidance.

The official `@drawio/mcp` server is intentionally **not** the default integration surface for this repository because its tool model does not match the offline-first edit/replicate workflow.

## License

This repository is licensed under **MIT** (see `LICENSE`).

The optional upstream next-ai-draw-io MCP server is licensed under **Apache-2.0**:

- <https://github.com/DayuanJiang/next-ai-draw-io/blob/main/LICENSE>
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